2019 Retail Tech Trends: predictive analytics

Retailers are using analytics software more than ever to drive efficiency and meet the demands of their customers. This year, we have even seen M&S launch its own retail data academy in order to bring its own staff up to digital speed. Clearly, predictive analysis has the power to change the retail environment further in 2019, but alongside opportunities come legal responsibilities that are associated with that most valuable asset: customer data.

Analytics programs and visualisation tools are a huge aid in bringing inefficiencies in the supply chain to the surface. Such tools have a range of applications from raw material production through to post-purchase customer care and marketing. The sources that can be used to gather retail data are also increasingly rich and varied, and now include Electronic Point of Sale (Epos) systems, smart beacons and in-store furniture from trolleys to security cameras and even shelves.

Not a sentence one utters everyday but yes, shelves are getting smarter. Modern interactive shelving can use dynamic and customisable LCD displays to catch the eye of the customer. There are also shelves that can receive shopping list information from a customers’ devices as they pass, and highlight on-shelf items that appear on their shopping lists. This can speed up the shopping experience and make it more pleasurable. Retailers are also experimenting with how shelves and other in-store fixtures and fittings can be equipped with facial recognition sensors that can gauge and analyse customer reaction to whatever is displayed on them or around them.

Epos systems are an obvious yet important means of capturing data. Walmart is known for instantly incorporating live point of sale data into its forecasting systems. This enables it very quickly to identify which products risk selling out and which are struggling, and to respond and plan accordingly. The customer experience is improved, as are its profit margins.

In mentioning Walmart it would be remiss not to touch on the recent publication of one of their trolley-related patents. The patent relates to a system for using sensors in trolley handles to measure customers’ heart rates to work out which areas in the store are most exciting – or most stressful perhaps!

Predictive analytics play a role beyond the store too, where examples might include identifying out of stock patterns, highlighting the impact of delays by various suppliers, and working out the most efficient routes and schedules for transport fleets to follow. Technology like IBM’s Watson or Microsoft Power BI can also be used to process complex data relating to issues like staff retention, enabling businesses to identify and hopefully address the causes of staff turnover. 

Of course, customer data is highly valuable to retailers and analytics has a part to play here too. By gathering and processing data on individuals, businesses gain insights into their preferences and buying patterns and can present each customer with a personalised experience. By targeting customers in this way, retailers can maximise their own opportunity for a sale.

While these predictive technologies do indeed enable retailers to increase sales and profitability, they can also make the buying experience more personal and pleasurable for customers. The increasing sophistication of personalisation means that retailers are getting better at presenting consumers with more of what they are interested in and less of what they aren’t.

There are drawbacks, however. Consumers realise that their personal data has become a valuable commodity. There are widespread concerns about the richness, depth and quantity of the data collected generally, about what it is used for and about how securely it is held.

This is where the GDPR and Data Protection Act 2018 come into play. Both increase the degree of control individuals have over their data. Individuals have numerous rights, including the right to erasure of their data, the right, essentially free of charge now, to receive a copy of all of their data and the right to object to profiling.  Predictive analysis using personal data is a form of profiling and is therefore something that the law does give an individual consumer the right to prevent.

Many retail businesses are using the fact that they process their customers’ personal data transparently and respectfully as a marketing tool in itself. Retailers can also gain an edge in the coming year by looking carefully at how to gather information that is genuinely anonymous and therefore does not engage data protection law at all. A key word here is “trust”. In this era of heightened sensitivity around data privacy, it is perhaps one of the most valuable commodities.